Data mining applications with R
(eBook)
Author:
Contributors:
Cen, Yonghua, author.
Published:
Amsterdam ; Boston : Academic Press, an imprint of Elsevier, 2013.
Format:
eBook
ISBN:
9780124115200, 0124115209, 9781306167796, 1306167795
Physical Desc:
1 online resource
Status:
Ebsco (CCU)
Description
Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries. Presents various case studies in real-world applications, which will help readers to apply the techniques in their work. Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves.
Copies
Ebsco (CCU)
Subjects
Bisac Subjects
OCLC Fast Subjects
Citations
APA Citation (style guide)
Zhao, Y., & Cen, Y. (2013). Data mining applications with R. Amsterdam ; Boston, Academic Press, an imprint of Elsevier.
Chicago / Turabian - Author Date Citation (style guide)Zhao, Yanchang, 1977- and Yonghua, Cen. 2013. Data Mining Applications With R. Amsterdam ; Boston, Academic Press, an imprint of Elsevier.
Chicago / Turabian - Humanities Citation (style guide)Zhao, Yanchang, 1977- and Yonghua, Cen, Data Mining Applications With R. Amsterdam ; Boston, Academic Press, an imprint of Elsevier, 2013.
MLA Citation (style guide)Zhao, Yanchang and Yonghua Cen. Data Mining Applications With R. Amsterdam ; Boston, Academic Press, an imprint of Elsevier, 2013.
Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Language:
English
Notes
General Note
Machine generated contents note: 1. Introduction 2. Case Study in Finance 3. Case Study in Retail 4. Case Study in Telecommunications 5. Case Study in Government 6. Case Study in Crime & Homeland Security 7. Case Study in Stock Market 8. Case Study in Social Welfare 9. Case Study in Social Media 10. Case Study in Sports 11. Case Study in Medicine and Health 12. Case Study in Bioinformatics 13. Case Study in Sentiment Analysis 14. Case Study in Spatial Data Analysis 15. Case Study in Patent Analysis 16. Case Study in Education 17. Case Study in Transport 18. Case Study in Real Estate Conclusions Bibliography.
Bibliography
Includes bibliographical references and index.
Description
Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries. Presents various case studies in real-world applications, which will help readers to apply the techniques in their work. Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves.
Staff View
Grouped Work ID:
5f15e626-0fda-4a69-1080-8c22974e5793
Record Information
| Last File Modification Time | May 07, 2024 09:09:05 PM |
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| Last Grouped Work Modification Time | May 07, 2024 08:57:32 PM |
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| 245 | 1 | 0 | |a Data mining applications with R /|c Yanchang Zhao, Senior Data Miner, RDataMining.com, Australia, Yonghua Cen, Associate Professor, Nanjing University of Science and Technology, China. |
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| 505 | 8 | |a 1. Power grid data analysis with R and Hadoop -- 2. Picturing Bayesian classifiers : a visual data mining approach to parameters optimization -- 3. Discovery of emergent issues and controversies in anthropology using text mining, topic modeling, and social network analysis of microblog content -- 4. Text mining and network analysis of digital libraries in R -- 5. Recommender systems in R -- 6. Response modeling in direct marketing : a data mining-based approach for target selection -- 7. Caravan insurance customer profile modeling with R -- 8. Selecting best features for predicting bank loan default -- 9. A Choquet integral toolbox and its application in customer preference analysis -- 10. A real-time property value index based on web data -- 11. Predicting seabed hardness using Random Forest in R -- 12. Supervised classification of images, applied to plankton samples using R and Zooimage -- 13. Crime analyses using R -- 14. Football mining with R -- 15. Analyzing Internet DNS(SEC) traffic with R for resolving platform optimization. | |
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